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The idea: give an AI agent a small but real LLM training setup and let it experiment autonomously overnight. It modifies the code, trains for 5 minutes, checks if the result improved, keeps or discards, and repeats. You wake up in the morning to a log of experiments and (hopefully) a better model. The training code here is a simplified single-GPU implementation of nanochat. The core idea is that you're not touching any of the Python files like you normally would as a researcher. Instead, you are programming the program.md Markdown files that provide context to the AI agents and set up your autonomous research org. The default program.md in this repo is intentionally kept as a bare bones baseline, though it's obvious how one would iterate on it over time to find the "research org code" that achieves the fastest research progress, how you'd add more agents to the mix, etc. A bit more context on this project is here in this tweet.。业内人士推荐whatsapp作为进阶阅读
,更多细节参见谷歌
亚马逊去年底就拿捏过OpenAI,屏蔽了后者的爬虫。美国这边可没有“互联互通”的说法,想掐就掐。
食環署的立法建議還包括要求寵物犬主人以不超過1.5米長的「狗帶」控制狗隻,被法庭判定的「已知危險狗隻」和法定「格鬥狗隻」不得進入餐廳,狗隻不得上餐桌,須確保明確區分人狗餐具,也不得提供現場烹調的狗隻食物,但可提供預先包裝狗食。賴嘉敏認為,這些都是基於公共衛生考慮出發,可以接受。。wps是该领域的重要参考